Relevance Feedback between Web Search and the Semantic Web

Halpin, Harry; Lavrenko, Victor

doi:10.5591/978-1-57735-516-8/IJCAI11-375

Relevance Feedback between Web Search and the Semantic Web

Harry Halpin, Victor Lavrenko

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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 2250-2254.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-375

Abstract

We investigate the possibility of using structured data to improve search over unstructured documents. In particular, we use relevance feedback to create a `virtuous cycle' between structured data gathered from the Semantic Web and web-pages gathered from the hypertext Web. Previous approaches have generally considered searching over the Semantic Web and hypertext Web to be entirely disparate, indexing and searching over different domains. Our novel approach is to use relevance feedback from hypertext Web results to improve Semantic Web search, and results from the Semantic Web to improve the retrieval of hypertext Web data. In both cases, our evaluation is based on certain kinds of informational queries (abstract concepts, people, and places) selected from a real-life query log and checked by human judges. We show our relevance model-based system is better than the performance of real-world search engines for both hypertext and Semantic Web search, and we also investigate Semantic Web inference and pseudo-relevance feedback.

Harry Halpin, and Victor Lavrenko. 2011. Relevance Feedback between Web Search and the Semantic Web. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 2250–2254. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-375

@inproceedings{ijcai2011p375,
  title     = {Relevance Feedback between Web Search and the Semantic Web},
  author    = {Halpin, Harry and Lavrenko, Victor},
  booktitle = {Proceedings of the Twenty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-11}},
  publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
  editor    = {Toby Walsh},
  pages     = {2250--2254},
  year      = {2011},
  month     = {7},
  doi       = {10.5591/978-1-57735-516-8/IJCAI11-375},
  url       = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-375},
}

TY  - CPAPER
TI  - Relevance Feedback between Web Search and the Semantic Web
AU  - Halpin, Harry
AU  - Lavrenko, Victor
T2  - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11
PB  - AAAI Press/International Joint Conferences on Artificial Intelligence
PY  - 2011
SP  - 2250
EP  - 2254
DO  - 10.5591/978-1-57735-516-8/IJCAI11-375
UR  - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-375
ER  -